This paper studies strong adaptive control problem of hypersonic morphing vehicles under the model uncertainty, external disturbance and non-minimum phase characteristics. Firstly, a dynamic model with uncertainties is con-structed, which is decomposed into a velocity system and an attitude system according to the characteristics of the model. An online parameter identification method based on modified forgetting factor is designed to obtain the ontology state, reduce the dependence on model knowledge, and provide real-time modal evaluation information for the controller. Then, a game-enhanced neural network observer is proposed to deal with the composite disturb-ance including identification error, variant uncertainty and external disturbance, so that the estimation error of the system can converge to the origin in a finite time. By designing the variable configuration-redefinition strategy to redefine the system output, the redefinition reference command under the variable configuration is given to avoid the unstable internal dynamics caused by the coupling of elevator and lift. Finally, the theoretical analysis of system stability is carried out based on Lyapunov stability theorem, and the effectiveness of the proposed method is veri-fied by simulation.
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